Skip to content

Instantly share code, notes, and snippets.

@marijnkoolen

marijnkoolen/crashflow_questions.md

Last active December 26, 2015 00:49
Show Gist options
  • Star 0 You must be signed in to star a gist
  • Fork 0 You must be signed in to fork a gist
  • Save marijnkoolen/7067028 to your computer and use it in GitHub Desktop.
Save marijnkoolen/7067028 to your computer and use it in GitHub Desktop.
Download ZIP
Raw
crashflow_questions.md

Questions

Step 0:

  • What is the title of your project?
  • what is the theme of your project?
  • what is the research question underlying your project?
  • what is the hypothesis of your project?
  • what is the domain?
  • what are core concepts of your project?
  • what are the relevant keywords?

Step 1 (acquiring):

  • which resources have data that is relevant to your research question?
  • how do these resources allow you to acquire relevant data?
    • searching and browsing
    • download whole collection
    • extract data through API
  • which API is appropriate for your project?
  • What is the data that you need from the API?
  • What query or queries would give you the data you need (think of the keywords you entered for step 0)?

Step 1b (reflecting on acquisition):

  • is the data from these sources sufficient for your research?
  • is the data from these sources complete and reliable?
  • what are limitations of acquiring data through the API?
  • what are limitations of the queries you can create?

Step 2 (parsing):

  • what type of data are you working with?
    • metadata description with multiple fields
    • natural language description (summary, review,)
    • full-text document
    • non-textual document (image, video, audio recording)
  • how is the data structured?
  • is the data structured consistently?

Step 3 (filtering):

  • from the data that the API returned, which parts do you need for your research?
  • which parts can be removed?

Step 4 (mine):

  • what kind of information do you want to get from each relevant part?
    • frequency of occurrence
    • frequency of co-occurrence
    • order of occurrence (timeline)

Step 5 (represent):

  • What kind of visual model would best allow you to analyse your data to answer your research question?

Step 6 (refine):

  • what are areas of interest in the representation that may need more detail?
  • what aspects of the representation would you like to highlight or represent differently?
  • what refinement methods would give focus to the areas of interest?
    • using different colours for data points in the area of interest.
    • zooming in on the areas of interest.
    • rotating the presentation

Step 7 (Interact):

  • how do you want to manipulate the data in the visualisation to be able to view it from different perspectives?
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment